Efficient fingerprint-based user authentication for embedded systems

User authentication, which refers to the process of verifying the identity of a user, is becoming an important security requirement in various embedded systems. While conventional solutions for user authentication have relied on password-based mechanisms, they are increasingly being replaced by biometric technologies such as fingerprint, face, and voice recognition, which are known to provide higher levels of security for user authentication. This paper investigates the problem of supporting efficient fingerprint-based user authentication in embedded systems. For improving the performance of fingerprint-based authentication, we propose hardware/software enhancements that include a generic set of custom instruction extensions to an embedded processor´s instruction set architecture, a memory-aware software re-design, and fixed-point arithmetic. We believe that the custom instruction set extensions proposed in this work are generic enough to speed up many fingerprint matching algorithms and even other biometric algorithms. Our experiments with an open-source, high-fidelity fingerprint authentication algorithm and a testbed featuring a commercial extensible processor show that performance is improved by a factor or 10.4X when using the proposed enhancements, while incurring modest overheads.